Is Matching Dimension Enough for Linear Transformation Invertibility?

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Discussion Overview

The discussion revolves around the conditions for the invertibility of linear transformations, specifically whether it is sufficient for the domain and codomain to have the same dimension or if they must be the same vector space. The scope includes theoretical considerations in linear algebra.

Discussion Character

  • Debate/contested

Main Points Raised

  • One participant questions whether the requirement for invertibility is that the domain and codomain must be the same vector space or merely have the same dimension.
  • Another participant clarifies that the range of the linear transformation must have the same dimension, not just the codomain, and notes that two vector spaces of the same dimension are isomorphic.
  • A different participant supports the initial intuition by stating that two vector spaces are isomorphic when they have the same dimension.
  • An example is provided where a specific function is described as an invertible linear transformation from R2 to P2, both having dimension 2, suggesting that different vector spaces can indeed be involved in invertible transformations.

Areas of Agreement / Disagreement

Participants express differing views on whether the same vector space is necessary for invertibility, indicating that multiple competing views remain on this topic.

Contextual Notes

There are nuances regarding the definitions of range and codomain, and the implications of isomorphism that are not fully resolved in the discussion.

Bipolarity
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For a linear transformation to be invertible, is it a requirement that the domain and codomain be the same vector space, or merely that they have the same dimension? My intuition tells me they merely need the same dimension but someone can correct me please?

BiP
 
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You have to be a bit careful - the range of the linear transformation needs to have the same dimension, not just the codomain. But there is no requirement they be exactly the same vector space (in fact two vector spaces which are the same dimension are always isomorphic, so in a sense they are the same vector space as far as any linear algebra operations go)
 
your intuition is correct. two vector spaces are isomorphic precisely when they have the same dimension.
 
For example, the function f(a, b)= a+ bx is an invertible linear transformation for R2, the vector space of ordered pairs of real numbers, to P2, the vector space of linear polynomials, both of which have dimension 2.
 

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